Sock designing and weaving integrated system and method

By constructing a test database and deep neural network model, the optimal beam pressure of sports socks was predicted, and the problem that existing sports socks were not optimized according to individual differences was solved, and the stability and comfort of sports socks were improved.

CN119294148AActive Publication Date: 2025-01-10SHANGRAO DAWAN NETWORK TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202411822954.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-12
Publication Date
2025-01-10
Estimated Expiration
2044-12-12

AI Technical Summary

Technical Problem

The existing sports socks’ goggle pressure data cannot be optimized according to individual differences, resulting in inappropriate goggle pressure, affecting sports performance and comfort.

Method used

By constructing a test database, we can obtain the tester's leg shape data and motion process data, calculate the beam port marks and slide data, establish the beam port pressure label, use the deep neural network model to predict the optimal beam port pressure data, and perform differentiated design and Production.

Benefits of technology

It realizes a differentiated design based on individual leg shape and exercise habits, provides optimal traction pressure, improves the stability and comfort of sports socks, and reduces strangulation and slippage.

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Abstract

The invention relates to the technical field of sock designing and weaving, in particular to a sock designing and weaving integrated system and method. Comprising the following steps: adjusting bundle pressure data, and producing to obtain a test sample; selecting a test person wearing the test sample to perform a motion test to obtain a test data set, and constructing a test database; according to the leg shape similarity between the leg shape data of the target person and the leg shape data of the test person, screening the test database to obtain a reference data set; according to the bundle tying mark data and the bundle sliding data in the reference data set, a bundle pressure label is obtained through measurement and calculation; performing model training according to the motion process data, the mouth binding pressure data and the mouth binding pressure label, and taking the corresponding leg shape similarity as a data weight to obtain a mouth binding pressure prediction model; and the historical motion data of the target person is identified according to the bundling pressure prediction model, and the optimal bundling pressure data is obtained. According to the method, the difference design and production of the sports socks can be accurately carried out on the target personnel through the optimal binding pressure data.
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Citation Information

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